AI/LLM/Machine Learning Engineer

Summary

An AI/Machine Learning Engineer at ZenGuard AI since February 2024, specializing in enhancing AI security. Developed LLM security guardrails using Python, PyTorch, Vertex AI, and spaCy, reducing prompt injection vulnerabilities by 95%. Improved AI model performance by 30% through advanced NLP techniques and integration with GCP vector databases. Increased system efficiency by 50% by engineering a concurrent rate limiter and automated model resilience testing across 20+ scenarios.

Expectations

Seeking a challenging role as an AI/Machine Learning Engineer where I can leverage my expertise in AI security, Large Language Models (LLMs), and advanced NLP techniques. I aim to contribute to projects that focus on enhancing AI model performance and security, utilizing technologies like Python, PyTorch, and cloud platforms such as Google Cloud Platform or Microsoft Azure. I'm looking for a collaborative environment that values innovation, continuous learning, and has a significant impact on system efficiency and resilience. My goal is to be part of a team where I can apply my skills to develop cutting-edge AI solutions that address real-world problems.

Employment Preferences

Expected Base Salary

**0,000 USD

Academic Degree

Experience

Skills

• Languages
• Python
• C
• Rust
• SQL
• AI
• ML
• PyTorch
• Scikit-learn
• Hugging Face
• Large Language Models
• LLMs
• NLP
• Computer Vision
• Cloud
• Tools
• Google Cloud Platform
• GCP
• Microsoft Azure
• Vertex AI
• GitHub Actions
• Docker
• Data
• Pandas
• Matplotlib
• Seaborn
• XML Parsing
• Data Analysis
• Visualization
• Security
• AI Security
• Prompt Injection Prevention
• Fraud Detection
• Frameworks
• Libraries
• SpaCy
• Asyncio
• Multithreading
• Operating Systems
• Unix
• Linux
• Software Development
• Git
• CI
• CD
• API Development
• Test Automation